The Machine Learning Safety Scholars program is a paid, 9-week summer program designed to help undergraduate students gain skills in machine learning with the aim of using those skills for empirical AI safety research in the future. Apply for the program here by May 31st.
The course will have three main parts:
The first two sections are based on public materials, and we plan to make the ML safety course publicly available soon as well. The purpose of this program is not to provide proprietary lessons but to better facilitate learning:
TL;DR—We’re distributing $20k in total as prizes for submissions that make effective arguments for the importance of AI safety. The goal is to generate short-form content for outreach to policymakers, management at tech companies, and ML researchers. This competition will be followed by another competition in around a month that focuses on long-form content.
This competition is for short-form arguments for the importance of AI safety. For the competition for distillations of posts, papers, and research agendas, see the Distillation Contest.
Objectives of the arguments
To mitigate AI risk, it’s essential that we convince relevant stakeholders sooner rather than later. To this end, we are initiating a pair of competitions to build effective arguments for a range of audiences. In particular, our audiences include policymakers, tech executives, and ML researchers.